Application of Fuzzy Delphi in the Selection of COPD Risk Factors among Steel Industry Workers.

BACKGROUND
The Delphi method has been widely applied in many study areas to systematically gather experts' input on particular topic. Recently, it has become increasingly well known in health related research. This paper applied the Fuzzy Delphi method to enhance the validation of a questionnaire pertaining chronic obstructive pulmonary disease (COPD) risk factors among metal industry workers.


MATERIALS AND METHODS
A detailed, predefined list of possible risk factors for COPD among metal industry workers was created through a comprehensive and exhaustive review of literature from 1995 to 2015. The COPD questionnaire were distributed among people identified as occupational, environmental, and hygiene experts. Linguistic variable using Likert scale was used by the expert to indicate their expert judgment of each item. Subsequently, the linguistic variable was converted into a triangular fuzzy number. The average score of the fuzzy number will be used to determine whether the item will be removed or retained.


RESULTS
Ten experts were involved in evaluating 26 items. The experts were in agreement with most of the items, with an average fuzzy number range between 0.429 and 0.800. Two items were removed and three items were added, leaving a total 26 items selected for the COPD risk factors questionnaire. The experts were in disagreement with each other for items F10 and F11 where most of the experts claimed that the question is too subjective and based on self-perception only.


CONCLUSION
The fuzzy Delphi method enhanced the accuracy of the questionnaire pertaining to COPD risk factors, and decreased the length of the established tools.


INTRODUCTION
The Delphi method was introduced in the 1950s in defense research, which was followed by application in societal, transportation, environmental, science, and technological research. It has become a fundamental tool for those in the area of technological forecasting and is used today in many technologically oriented corporations (1). Recently, The Delphi method has been widely applied for systematically gathering experts' input on a particular topic, especially in health related research, as this method is particularly well suited to health issues (2). The Delphi method has been used in occupational health research (3). Dapari R,et al. 47 Tanaffos 2017; 16 (1): [46][47][48][49][50][51][52] Subsequently the Delphi research method has become widely used in healthcare research (4).

TANAFFOS
The Delphi method is an iterative process for collecting and distilling anonymous experts' judgments using a series of data collection and analysis techniques interspersed with a feedback mechanism (5). The Delphi method has undergone steady development and modification since its inception in the 1950s (2). Over the years, many labels describing types of Delphi have been used. Some labels relate to the type of application, some to the method of scoring used, and some just imply a difference in approach (6). The fuzzy Delphi method is one example from numerous Delphi methods that have undergone modification and development. The fuzzy Delphi method is a combination of the traditional Delphi method and Fuzzy Set Theory, which aims to address some of the ambiguity of the expert panel consensus. It is a more advanced version of the Delphi method in that it utilizes triangulation statistics to determine the distance between the levels of consensus within the expert panel (7).
Furthermore, the objective of using Delphi is to achieve group consensus (6). In general, an expert could be anyone with relevant input.
Some applications require panels covering a wide range of interests and disciplinary viewpoints (1). However, since expert opinion is sought, a purposive sample may be necessary. It may begin with the researcher seeking help from a supervisor to identify the initial group of experts, followed by using a "snowball" sampling technique to generate a subsequent expert panel (5). Fortunately, in many health-related problems, the identity of these experts is commonly acknowledged within the circle of health professionals and the Delphi panel can be recruited swiftly and without controversy (2). Although it is clear that the selected experts are multifaceted, there will continue to be difficulties in defining and justifying their selection (9). In chronic inflammatory response in the airways (12). COPD is a complex, multifactorial, and progressive disease and is now known to be the most frequent chronic disease in developing country workers (13). In Malaysia, the prevalence of moderate to severe COPD in persons 30 years and older is 4.7% (14). Occupational exposures is one the factors associated with COPD (15), for example exposure to dusts, noxious gases/vapors, fumes (16), and metal dust (17). Smelters and furnace workers have the highest prevalence of COPD followed by casters and other professional groups (13). Throughout the world, many people suffer from COPD for many years, and die prematurely from it or its associated complications (12).
The disease is causing rising economic burden (18), especially in developing countries (19).    provide additional items if they believe that the item is necessary to attain the study objective. Then, the item will be included for the next round and the expert panel will

MATERIALS AND METHODS
give a score. The cycle will be repeated until there is no more additional input from the expert panel.

Ethics
These studies were reviewed and approved by ethics committee of the National University of Malaysia (FF-2015-318).

Analysis of the experts' judgment using the Fuzzy
Delphi method yielded the following findings ( Table 2).
The experts were in agreement with most of the items with an average fuzzy number range between 0.429 and 0.800.
Two items were removed and three items were added leaving a total of 24 items, which were selected for the

DISCUSSION
The purpose of this study was to examine the extent of experts' consensus on the risk factors of COPD among metal industry workers. The experts were in disagreement with each other regarding whether the workers or coworkers can smell something while being exposed to metal dust (see items F10 and F11). As the score of these items were below 0.6, items F10 and F11 were excluded from the COPD risk factor questionnaire. Item F10 asks, "Can you smell something while you are exposed to metal dust?" and item F11 asks, "Do any of your friend ever complain to you that they smell something while being exposed to metal dust?" The final scores were 0.486 and 0.429, respectively. This indicates that the expert panels believed that the questions were too subjective, depending on the workers' perception. Therefore, the response from the respondent would not help to establish whether they had been exposed to metal dust.

Strengths and limitations
The

Recommendation
Selecting experts who have had significant experience with the intervention approach and having a balanced number of experts with similar job scope will help to improve the validity of these findings. This research study may elicit more related studies on the application of the fuzzy Delphi method to evaluate and establish questionnaires on health related issues. The fuzzy Delphi method has been, and will continue to be, an important data collection methodology with a wide variety of applications and uses for people who want to gather information from experts in a particular subject.

CONCLUSION
The application the fuzzy Delphi method by conducting an expert survey and analyzing the results in selection COPD risk factors helps to enhance the validity and shorten the duration of established tools. The result from this study will serve as a foundation for the construction of further content validation through pre-tests and pilot studies.